Evidence map›Paper›PMID 30616521›Full record

ArticleBMC bioinformatics2019

GeNeCK: a web server for gene network construction and visualization.

Minzhe Zhang, Qiwei Li, Donghyeon Yu, Bo Yao, Wei Guo, Yang Xie, Guanghua Xiao

Abstract read
In one paragraph

Article in BMC bioinformatics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.

0numbers the graph read from it
0cells of the map it votes in
24citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

24 citing papers in PubMed.

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  11. NETISCE: a network-based tool for cell fate reprogramming.NPJ systems biology and applications · 2022
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Minzhe ZhangQuantitative Biomedical Research Center, University of Texas Southwestern Medical Center, 5323 Harry Hines Blvd., Dallas, 75390, TX, United States.
Qiwei LiQuantitative Biomedical Research Center, University of Texas Southwestern Medical Center, 5323 Harry Hines Blvd., Dallas, 75390, TX, United States.
Donghyeon YuDepartment of Statistics, Inha University, Incheon, South Korea.
Bo YaoQuantitative Biomedical Research Center, University of Texas Southwestern Medical Center, 5323 Harry Hines Blvd., Dallas, 75390, TX, United States.
Wei GuoBioHPC team, Lyda Hill Department of Bioinformatics, University of Texas Southwestern Medical Center, 5323 Harry Hines Blvd., Dallas, Texas, United States.
Yang XieQuantitative Biomedical Research Center, University of Texas Southwestern Medical Center, 5323 Harry Hines Blvd., Dallas, 75390, TX, United States.
Guanghua XiaoQuantitative Biomedical Research Center, University of Texas Southwestern Medical Center, 5323 Harry Hines Blvd., Dallas, 75390, TX, United States. Guanghua.Xiao@UTSouthwestern.edu.ORCID http://orcid.org/0000-0001-9387-9883

Funding

UNIVERSITY OF TEXAS--SPORE IN LUNG CANCERP50CA070907 · NCI · UT SOUTHWESTERN MEDICAL CENTER · PI GIBBONS, DON LYNN · 1996 to 2024
$57.4M
Integrative Analysis to Identify Therapeutic Targets for Lung CancerR01CA172211 · NCI · UT SOUTHWESTERN MEDICAL CENTER · PI XIAO, GUANGHUA · 2013 to 2017
$1.6M
Integrative Analysis to Identify Regulation Targets of RNA-Binding ProteinsR01GM115473 · NIGMS · UT SOUTHWESTERN MEDICAL CENTER · PI XIE, YANG · 2016 to 2019
$1.3M
Dissection of the Modular Structure of Cancer Signaling SystemsR33CA120732 · NCI · STANFORD UNIVERSITY · PI MEYER, TOBIAS · 2008 to 2010
$935k
Dissection of the Modular Structure of Cancer Signaling SystemsR21CA120732 · NCI · STANFORD UNIVERSITY · PI MEYER, TOBIAS · 2006 to 2006
$359k
Cancer Prevention and Research Institute of Texas RP120732NCI NIH HHS P50 CA070907NCI NIH HHS R01 CA172211NIGMS NIH HHS R01 GM115473NIH HHS 1R01CA172211NIH HHS 1R01GM115473NIH HHS 5P50CA070907
6 · The paper itself

Abstract

backgroundReverse engineering approaches to infer gene regulatory networks using computational methods are of great importance to annotate gene functionality and identify hub genes. Although various statistical algorithms have been proposed, development of computational tools to integrate results from different methods and user-friendly online tools is still lagging.

resultsWe developed a web server that efficiently constructs gene networks from expression data. It allows the user to use ten different network construction methods (such as partial correlation-, likelihood-, Bayesian- and mutual information-based methods) and integrates the resulting networks from multiple methods. Hub gene information, if available, can be incorporated to enhance performance.

conclusionsGeNeCK is an efficient and easy-to-use web application for gene regulatory network construction. It can be accessed at http://lce.biohpc.swmed.edu/geneck .

Indexed as

Computer GraphicsGene Regulatory NetworksInternetProtein Interaction MapsSoftwareAlgorithmsBayes TheoremComputational BiologyHumansTranscriptomeBayesianCorrelationEnsembleGene networkHub geneLikelihoodMutual informationStatistical methodVisualizationWeb server

Identifiers

PMID30616521
PMCPMC6323745

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.